This statistic shows the year-over-year change of real disposable income in the United States from 2016 to 2021 and gives a forecast through 2027. In 2022, real disposable income is projected to decrease by **** percent compared to the previous year.

Abstract

The startling drop in incomes and increase in inequality accompanying the transition to market economies in Eastern Europe and the former Soviet Union raise critical questions: Who is most likely to be poor? How well are existing social assistance programs reaching those who most need help? And what kind of programs would be most effective in reducing poverty? As part of a project analyzing poverty and social assistance in the transition economies, a Bank research team created a database of household expenditure and income data from recent surveys - the HEIDE database. (See the book by J. Braithwaite, Ch. Grootaert and B. Milanovic, "Poverty and social assistance in Transition Countries, St. Martin's Press, 1999" and the book by B. Milanovic, Income, inequality, and poverty during the transition from planned to market economy, World Bank, 1998.)

The HEIDE database includes four countries in both Eastern Europe and the Former Soviet Union. Latvia was then added at a later stage.

The four files are: -hhold: Household data consists of the variables in Variable List at household level. -ind: Individual data consists of the variables in Variable List at individual level. -modelh: Household data consists of the variables used in regression models. -modeli: Individual data consists of the variables used in regression models.

Prefixes are used to indicate countries for the data files, i.e. A- Rural Armenia B- Bulgaria E- Estonia H- Hungary K- Kyrgyz P- Poland R- Russia S- Slovak Y- Urban Armenia

The survey data were cleaned for possible inconsistencies and errors and adjusted for missing data and outliers. The compilation of almost 100 variables with similar definitions for the eight countries allows ready cross-country analysis and comparisons. A consistent syntax is used for the variables to enable researchers to use the same macro routines across countries. There are more than 3 million data points.

Geographic coverage

The database includes data from Armenia, Bulgaria, Estonia, Hungary, Kyrgyz Republic, Latvia, Poland, Russia, and the Slovak Republic.

Kind of data

Sample survey data [ssd]

Mode of data collection

Face-to-face [f2f]

Cleaning operations

The survey data were cleaned for possible inconsistencies and errors and adjusted for missing data and outliers. The compilation of almost 100 variables with similar definitions for the eight countries allows ready cross-country analysis and comparisons.

See document "Household Expenditure and Income Data for Transitional Economies (HEIDE): Data Cleaning and Rent Imputation - Appendix 1 of RAD project "Poverty and Targeting of Social Assistance in Eastern Europe and the Former Soviet Union"".

Household income in India was drastically impacted due to the coronavirus (COVID-19) lockdown as of April 12, 2020. There was a significant decrease in the level of income with households reporting a fall in income from about nine percent in late February to a whopping 45.7 percent in mid April. Rise in income saw a contrasting trend indicating similar results; from 31 percent in late February to 10.6 percent on April 12, 2020.

The country went into lockdown on March 25, 2020, the largest in the world, restricting 1.3 billion people, extended until May 3, 2020. For further information about the coronavirus (COVID-19) pandemic, please visit our dedicated Fact and Figures page.

United States CCI: 6 Months Expectations: sa: Income: Decrease data was reported at 18.200 % in Apr 2025. This records an increase from the previous number of 14.900 % for Mar 2025. United States CCI: 6 Months Expectations: sa: Income: Decrease data is updated monthly, averaging 8.600 % from Feb 1967 (Median) to Apr 2025, with 637 observations. The data reached an all-time high of 24.000 % in Feb 2009 and a record low of 4.600 % in Apr 1967. United States CCI: 6 Months Expectations: sa: Income: Decrease data remains active status in CEIC and is reported by The Conference Board. The data is categorized under Global Database’s United States – Table US.H049: Consumer Confidence Index. [COVID-19-IMPACT]

Russia Household Income Use: % of Total: Increase/Decrease Cash on Hand data was reported at -0.100 % in Nov 2018. This records an increase from the previous number of -3.100 % for Oct 2018. Russia Household Income Use: % of Total: Increase/Decrease Cash on Hand data is updated monthly, averaging 1.400 % from Jan 1996 (Median) to Nov 2018, with 275 observations. The data reached an all-time high of 13.500 % in Dec 2006 and a record low of -21.400 % in Jan 2009. Russia Household Income Use: % of Total: Increase/Decrease Cash on Hand data remains active status in CEIC and is reported by Federal State Statistics Service. The data is categorized under Russia Premium Database’s Household Survey – Table RU.HA013: Household Income Use.

Graph and download economic data for Real Disposable Personal Income (DSPIC96) from Jan 1959 to May 2025 about disposable, personal income, personal, income, real, and USA.

Income share held by highest 20% of Cabo Verde slumped by 8.63% from 53.30 % in 2007 to 48.70 % in 2015. Since the 8.10% drop in 2007, income share held by highest 20% dropped by 8.63% in 2015. Percentage share of income or consumption is the share that accrues to subgroups of population indicated by deciles or quintiles. Percentage shares by quintile may not sum to 100 because of rounding.

In 2024, the average annual per capita disposable income of households in China amounted to approximately 41,300 yuan. Annual per capita income in Chinese saw a significant rise over the last decades and is still rising at a high pace. During the last ten years, per capita disposable income roughly doubled in China. Income distribution in China As an emerging economy, China faces a large number of development challenges, one of the most pressing issues being income inequality. The income gap between rural and urban areas has been stirring social unrest in China and poses a serious threat to the dogma of a “harmonious society” proclaimed by the communist party. In contrast to the disposable income of urban households, which reached around 54,200 yuan in 2024, that of rural households only amounted to around 23,100 yuan. Coinciding with the urban-rural income gap, income disparities between coastal and western regions in China have become apparent. As of 2023, households in Shanghai and Beijing displayed the highest average annual income of around 84,800 and 81,900 yuan respectively, followed by Zhejiang province with 63,800 yuan. Gansu, a province located in the West of China, had the lowest average annual per capita household income in China with merely 25,000 yuan. Income inequality in China The Gini coefficient is the most commonly used measure of income inequality. For China, the official Gini coefficient also indicates the astonishing inequality of income distribution in the country. Although the Gini coefficient has dropped from its high in 2008 at 49.1 points, it still ranged at a score of 46.5 points in 2023. The United Nations have set an index value of 40 as a warning level for serious inequality in a society.

Secondary income receipts of Chad jumped by 8.83% from 192,426,556 US dollars in 1993 to 209,412,854 US dollars in 1994. Since the 9.96% drop in 1991, secondary income receipts went down by 2.82% in 1994. Current transfers (receipts) are recorded in the balance of payments whenever an economy receives goods, services, income, or financial items without a quid pro quo. All transfers not considered to be capital are current. Data are in current U.S. dollars.

Abstract The Brazilian economy continues presenting the most unequal distribution of income among all countries in the world. The article presents the consequences of the growing disparities and considers the pros and cons of the introduction of a Guaranteed Minimum Income Program, through a negative income tax, as an efficient instrument to remove poverty. The second part of this work identifies an analytical structure which could reproduce the effects, on the level of the productive structure, of a process of Income Distribution. The aim was achieved as a result of the choice of an Input-Output Model which used an enlargement of the basic Leontief (1951) Model, from a derivation of social accounting matrix, as resulted in an estimation of the disaggregated multipliers for production, income and employment.

This paper aims to systematize the explanations for income inequality decreases observed in Brazil between 2001 and 2015, analyzing each region and subperiod separately and focusing on social programs. The results indicate that social program incomes, as well as pension incomes, have gained prominence as income sources relative to labor income. Social program incomes contributed 19% to income inequality decreases, especially in the North and Northeast, between 2001-2004 and 2008-2012. However, this contribution declined in the Northeast and increased in the Southeast at the beginning of the great recession. Labor income contributed 57% to income inequality decreases and explains why a sharper decrease was noted in the South and Center-West regions. Official pensions contributed 17% to inequality reductiomn in all Brazilian regions, more strongly between 2004 and 2012, when significant minimum wage increases occurred.

Serbia RS: Proportion of People Living Below 50 Percent Of Median Income: % data was reported at 12.400 % in 2021. This records a decrease from the previous number of 14.600 % for 2020. Serbia RS: Proportion of People Living Below 50 Percent Of Median Income: % data is updated yearly, averaging 18.700 % from Dec 2012 (Median) to 2021, with 10 observations. The data reached an all-time high of 21.600 % in 2014 and a record low of 12.400 % in 2021. Serbia RS: Proportion of People Living Below 50 Percent Of Median Income: % data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Serbia – Table RS.World Bank.WDI: Social: Poverty and Inequality. The percentage of people in the population who live in households whose per capita income or consumption is below half of the median income or consumption per capita. The median is measured at 2017 Purchasing Power Parity (PPP) using the Poverty and Inequality Platform (http://www.pip.worldbank.org). For some countries, medians are not reported due to grouped and/or confidential data. The reference year is the year in which the underlying household survey data was collected. In cases for which the data collection period bridged two calendar years, the first year in which data were collected is reported.;World Bank, Poverty and Inequality Platform. Data are based on primary household survey data obtained from government statistical agencies and World Bank country departments. Data for high-income economies are mostly from the Luxembourg Income Study database. For more information and methodology, please see http://pip.worldbank.org.;;The World Bank’s internationally comparable poverty monitoring database now draws on income or detailed consumption data from more than 2000 household surveys across 169 countries. See the Poverty and Inequality Platform (PIP) for details (www.pip.worldbank.org).

Indonesia Sharia Life Insurance: Income: Decrease (Increase) Allowance for Contributions and PAKYBMP: Decrease (increase) PAKYBMP data was reported at -35.789 IDR bn in Apr 2023. This records an increase from the previous number of -44.213 IDR bn for Mar 2023. Indonesia Sharia Life Insurance: Income: Decrease (Increase) Allowance for Contributions and PAKYBMP: Decrease (increase) PAKYBMP data is updated monthly, averaging -9.746 IDR bn from Aug 2017 (Median) to Apr 2023, with 69 observations. The data reached an all-time high of 36.317 IDR bn in Nov 2017 and a record low of -66.352 IDR bn in Sep 2017. Indonesia Sharia Life Insurance: Income: Decrease (Increase) Allowance for Contributions and PAKYBMP: Decrease (increase) PAKYBMP data remains active status in CEIC and is reported by Indonesia Financial Services Authority. The data is categorized under Indonesia Premium Database’s Insurance Sector – Table ID.RGF016: Insurance Statistics: Sharia Life Insurance: Income Statement.

Objective: Income volatility presents a growing public health threat. To our knowledge, no previous study examined the relationship between income volatility, cognitive function and brain integrity. Methods: We studied 3,287 participants aged 23 to 35 years in 1990 from the Coronary Artery Risk Development in Young Adults prospective cohort study. Income volatility data were created using income data collected from 1990 to 2010 and defined as standard deviation of percent change in income and number of income drops >=25% (categorized as 0, 1, or 2+). In 2010, cognitive tests (n=3,287) and brain scans (n=716) were obtained. Results: After covariate adjustment, higher income volatility was associated with worse performances on processing speed (β=-1.09, 95%CI=-1.73, -0.44) and executive functioning (β=2.53, 95%CI:0.60, 4.50) but not on verbal memory (β=-0.02, 95%CI:-0.16, 0.11). Similarly, additional income drops were associated with worse performances on processing speed and executive functioning. Higher income volatility and more income drops were also associated with worse microstructural integrity of total brain and total white matter. All findings were similar when restricted to those with high education, suggesting reverse causation may not explain these findings. Conclusion: Income volatility over a 20-year period of formative earning years was associated with worse cognitive function and brain integrity in midlife.

The median income of homebuyers in the United States grew steadily over the last decade, despite a brief drop in 2021. In 2023, the median income of reached ******* U.S. dollars. This was an increase of over ****** U.S. dollars in just 10 years.

Survey on Households and the Environment: Percentage of persons aged 16 years old and more who usually walk or cycle, by net monthly household income and reasons commuting using these means. National.

Secondary income receipts of Finland rocketed by 21.17% from 2,514,130,647 US dollars in 2023 to 3,046,365,160 US dollars in 2024. Since the 6.70% drop in 2020, secondary income receipts shot up by 68.09% in 2024. Current transfers (receipts) are recorded in the balance of payments whenever an economy receives goods, services, income, or financial items without a quid pro quo. All transfers not considered to be capital are current. Data are in current U.S. dollars.

(StatCan Product) This information product has been customized to present family data including income by Census Family Type for the year 2017 by Postal Area and Postal Walk.

Key information about Brazil Household Income per Capita

• Brazil Annual Household Income per Capita reached 4,779.705 USD in Dec 2017, compared with the previous value of 4,272.395 USD in Dec 2016.
• Brazil Annual Household Income per Capita data is updated yearly, available from Dec 2016 to Dec 2017, with an averaged value of 4,526.050 USD.
• The data reached an all-time high of 4,779.705 USD in Dec 2017 and a record low of 4,272.395 USD in Dec 2016.
• In the latest reports, Retail Sales of Brazil dropped 2.265 % YoY in May 2023.

CEIC calculates Annual Household Income per Capita from Monthly Household Income per Capita multiplied by 12 and converts it into USD. The Brazilian Institute of Geography and Statistics provides Monthly Household Income per Capita in local currency. Federal Reserve Board average market exchange rate is used for currency conversions.

Key information about South Korea Household Income per Capita

• South Korea Annual Household Income per Capita reached 19,208.928 USD in Dec 2024, compared with the previous value of 19,230.954 USD in Dec 2023.
• South Korea Annual Household Income per Capita data is updated yearly, available from Dec 2003 to Dec 2024, with an averaged value of 14,290.376 USD.
• The data reached an all-time high of 19,230.954 USD in Dec 2023 and a record low of 7,685.194 USD in Dec 2003.
• In the latest reports, Retail Sales of South Korea dropped 0.473 % YoY in May 2023.

CEIC calculates Annual Household Income per Capita from quarterly Monthly Household Income multiplied by 3 and quarterly Average Household Size and converts it into USD. Statistics Korea provides Household Income in local currency and Average Household Size. Federal Reserve Board average market exchange rate is used for currency conversions. Household Income excludes single person and farm households. Household Income per Capita prior to 2019 is based on old methodology.